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Articole: 71
  1. Background In a previous post, Constraints and Assertions, we introduced the idea of using constraints to verify input, output and intermediate datasets for an analytical process.

  2. WritableTestCase: Example Use

    In my PyCon UK talk yesterday I promised to update the and document the copy of writabletestcase.WritableTestCase on GitHub.

  3. Python UK 2016, Cardiff.

  4. Extracting More Apple Health Data

    The first version of the Python code for extracting data from the XML export from the Apple Health on iOS neglected to extract Activity Summaries and Workout data.

  5. Unit Tests

    In the last post, we presented some code for implementing a "reference" test for the code for extracting CSV files from the XML dump that the Apple Health app on iOS can produce.

  6. First Test

    In the last post, I presented some code for extracting (some of) the data from the XML file exported by the Apple Health app on iOS, but—almost comically, given this blog's theme—omitted to include any tests.

  7. I'm going to present a series of posts based around the sort of health and fitness data that can now be collected by some phones and dedicated fitness trackers.

  8. Lessons Learned: Bad Data and other SNAFUs

    My first paid programming job was working for my local education authority during the summer.

  9. Guest Post by Patrick Surry, Chief Data Scientist, Hopper Every year, Expedia and ARC collaborate to publish some annual statistics about domestic airfare, including their treatment of the perennial question "How far in advance should you book your flight…

  10. Tools and Tooling

    Good tools for testing matter because the temptation to skimp on testing is real even for true believers: anything that reduces the friction and pain associated with actually adding tests therefore has a disproportionate effect on adoption and implementat…

  11. Everyone building predictive models or performing statistical fitting knows about overfitting.

  12. We have an overview piece in Predictive Analytics Times this week.

  13. Anomaly Detection

    The Broader Process: Anomaly detection and Alerting.

  14. Unit Testing

    Systematic Unit Tests, System Tests and Reference Tests The third major idea in test-driven data analysis is the one most directly taken from test-driven development, namely systematically developing both unit tests for small components of the analytical…

  15. Constraints and Assertions

    Consistency Checking of Inputs, Outputs and Intermediates While the idea of regression testing comes straight from test-driven development, the next idea we want to discuss is associated more with general defensive progamming than TDD.

  16. Site News: Glossary; Table of Contents; Feeds

    The site now has a glossary, and also a table of contents, both linked from the side panel (which is at the top on mobile).

  17. Infinite Gain: The First Test

    The first idea we want to appropriate from test-driven development is that of regression testing, and our specific analytical variant of this, the idea of a reference test.

  18. How is this Misleading Data Misleading Me?

    "Why is this lying bastard lying to me?"

  19. Test-Driven Development: A Review

    Since a key motivation for developing test-driven data analysis (TDDA) has been test-driven development (TDD), we need to conduct a lightning tour of TDD before outlining how we see TDDA developing.

  20. Why Test-Driven Data Analysis?

    OK, everything you need to know about TeX has been explained—unless you happen to be fallible.

  21. Test-Driven Data Analysis

    A dozen or so years ago I stumbled across the idea of test-driven development from reading various posts by Tim Bray on his Ongoing blog.